Abstract of presentation at 5th Biennial on Negotiation, Novancia Business School Paris, 24 March 2014.

1. Can machines replace human negotiators?
Negotiators exchange messages, process and evaluate data, make concessions, impose
conditions, make tradeoffs, accept or reject proposals, make counter-proposals, decide
whether to close a deal or walk away.
Machines can perform all of these tasks better than human agents. Computers are not prone
to misunderstanding and do not lie, bluff, threaten or lose their tempers.
Take e-bay’s automated bidding system. Bidder A can bid $10 for an item and set a
maximum amount he is ready to pay, say $50. As other bidders make higher offers, the
system will trump them incrementally up to the maximum set by Bidder A, who will either
get the item at the optimal price (one increment above the highest competing bid) or
abandon the bidding process once the maximum amount is reached.
Such efficiency would be impossible in a traditional auction, where emotion might prompt a
bidder to pay more for an item than originally intended or back off in the face of an
aggressive competitor.
While e-commerce, albeit of a primitive kind (the sole variable is price) has become
widespread in B2C and C2C transactions, it does not appear to have made the same inroads
in B2B negotiations as in other aspects of business (catalogue, inventory and procurement
management) although it is technically possible to automate B2B negotiations for variables
other than price, such as discount, delivery time, incoterms, payment terms, warranty and
maintenance. There are only two differences between our e-bay example and a B2B
scenario: in the former, there is one variable (price) and only one party makes concessions
(the bidder). In automated B2B negotiations, both sides need to make concessions and there
are multiple variables.
If we compare human and automated B2B negotiations, the main differences are that the
former use natural language, include messages that are ambiguous or irrelevant to the
object of the negotiation and rely on subjective evaluations and partial decisions, whereas
the latter use machine language, focus exclusively on the variables at hand and make
objective evaluations and impartial decisions.
Academics and others who write about negotiation tend to deal only with human
negotiation and steer clear of automated negotiation, which is the preserve of
mathematicians, experts in artificial intelligence and game theory. An Amazon search (June
2013) gives 88 results for “B2B Negotiation” and 2 results for “Automated B2B Negotiation”.
While much work has been done on the subject of automated negotiation, it is often
abstract, inaccessible to the layman and not directly applicable in terms of deployment of
the technology in B2B negotiations.
Despite the existence of a global e-commerce infrastructure that could support automated
negotiation, most B2B negotiations are still conducted by human agents in the same way
they have been for centuries: through face-to-face discussions.
This paper describes what automated negotiation is, gives an overview of its development,
explores the benefits it can bring to B2B transactions and examines the challenges and
limitations involved in replacing human negotiators by machines.